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Quantitative Evaluation of High-Tech Industry Policies Based on the PMC-Index Model: A Case Study of China’s Beijing-Tianjin-Hebei Region

Author

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  • Yiwen Liu

    (School of Management, Tianjin University of Technology, Tianjin 300384, China)

  • Jian Li

    (School of Management, Tianjin University of Technology, Tianjin 300384, China
    College of Management and Economics, Tianjin University, Tianjin 300072, China)

  • Yi Xu

    (School of Management, Tianjin University of Technology, Tianjin 300384, China)

Abstract

High-tech industrial agglomeration plays a significant role in regional sustainable development. Local governments have issued many industrial policies to accelerate the development of high-tech industries in China. Evaluating high-tech industry policies from the perspective of regional industrial synergy can prevent problems in policy implementation and promote the industrial synergy in a region. For this purpose, taking China’s Beijing-Tianjin-Hebei (BTH) region as a case, we evaluate seven policies governing the high-tech industry in this region by using the approach which integrates the policy modeling consistency index (PMC-Index) model and text mining. We propose an evaluation system with consideration of regional industrial synergy, which is based on the PMC-Index model. The results show that the lowest PMC-Index value of the seven policies is 5.30, the highest is 8.17, and the average is 6.67. Among the policies, four are of excellent or perfect grade and relatively comprehensive; three are of acceptable grade and relatively insufficient. The overall designs of the high-tech industrial policies are reasonable but there is still much room for improvement. According to the average scores of the main indicators, the policies function relatively poorly in terms of policy release agency, policy timeliness, policy type and policy receptor. The optimizations for the shortcomings of each policy are also suggested. This study may not only provide some enlightenment to policymakers, but also provide a supplement for the policy evaluation field.

Suggested Citation

  • Yiwen Liu & Jian Li & Yi Xu, 2022. "Quantitative Evaluation of High-Tech Industry Policies Based on the PMC-Index Model: A Case Study of China’s Beijing-Tianjin-Hebei Region," Sustainability, MDPI, vol. 14(15), pages 1-17, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:15:p:9338-:d:875779
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    as
    1. Miriam Bruhn & David McKenzie, 2019. "Can Grants to Consortia Spur Innovation and Science-Industry Collaboration? Regression- Discontinuity Evidence from Poland," The World Bank Economic Review, World Bank, vol. 33(3), pages 690-716.
    2. Fang Liu & Zhi Liu, 2022. "Quantitative Evaluation of Waste Separation Management Policies in the Yangtze River Delta Based on the PMC Index Model," IJERPH, MDPI, vol. 19(7), pages 1-24, March.
    3. Youzhu Li & Rui He & Jinsi Liu & Chongguang Li & Jason Xiong, 2021. "Quantitative Evaluation of China’s Pork Industry Policy: A PMC Index Model Approach," Agriculture, MDPI, vol. 11(2), pages 1-21, January.
    4. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    5. Tinglin Zhang & Bindong Sun & Wan Li & Huimin Zhou, 2022. "Information communication technology and manufacturing decentralisation in China," Papers in Regional Science, Wiley Blackwell, vol. 101(3), pages 619-637, June.
    6. Wenbo Ma & Weiteng Tian & Qian Zhou & Qianqian Miao & Wei Zhang, 2021. "Analysis on the Temporal and Spatial Heterogeneity of Factors Affecting Urbanization Development Based on the GTWR Model: Evidence from the Yangtze River Economic Belt," Complexity, Hindawi, vol. 2021, pages 1-11, October.
    7. Huang, Siyu & Shi, Yi & Chen, Qinghua & Li, Xiaomeng, 2022. "The growth path of high-tech industries: Statistical laws and evolution demands," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    8. Pan, Wenrong & Xie, Tao & Wang, Zhuwang & Ma, Lisha, 2022. "Digital economy: An innovation driver for total factor productivity," Journal of Business Research, Elsevier, vol. 139(C), pages 303-311.
    9. Yang, Chao & Huang, Cui & Su, Jun, 2020. "A bibliometrics-based research framework for exploring policy evolution: A case study of China's information technology policies," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    10. Hao, Yan & Zhang, Menghui & Zhang, Yan & Fu, Chenling & Lu, Zhongming, 2018. "Multi-scale analysis of the energy metabolic processes in the Beijing–Tianjin–Hebei (Jing-Jin-Ji) urban agglomeration," Ecological Modelling, Elsevier, vol. 369(C), pages 66-76.
    11. Xianzhong Cao & Bo Chen & Yuefang Si & Senlin Hu & Gang Zeng, 2021. "Spatio-temporal evolution and mechanism of regional innovation efficiency: Evidence from Yangtze River Delta Urban Agglomeration of China," PLOS ONE, Public Library of Science, vol. 16(7), pages 1-13, July.
    12. Ruiz Estrada, Mario Arturo, 2011. "Policy modeling: Definition, classification and evaluation," Journal of Policy Modeling, Elsevier, vol. 33(4), pages 523-536, July.
    13. Shengli Dai & Weimin Zhang & Jiamin Zong & Yingying Wang & Ge Wang, 2021. "How Effective Is the Green Development Policy of China’s Yangtze River Economic Belt? A Quantitative Evaluation Based on the PMC-Index Model," IJERPH, MDPI, vol. 18(14), pages 1-17, July.
    14. Li, Lan-bing & Liu, Bing-lian & Liu, Wei-lin & Chiu, Yung-Ho, 2017. "Efficiency evaluation of the regional high-tech industry in China: A new framework based on meta-frontier dynamic DEA analysis," Socio-Economic Planning Sciences, Elsevier, vol. 60(C), pages 24-33.
    15. Tong Zhao & Zhijie Song & Tianjiao Li, 2018. "Effect of innovation capacity, production capacity and vertical specialization on innovation performance in China's electronic manufacturing: Analysis from the supply and demand sides," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-23, July.
    16. Dani Rodrik, 2019. "Where Are We in the Economics of Industrial Policies?," Frontiers of Economics in China-Selected Publications from Chinese Universities, Higher Education Press, vol. 14(3), pages 329-335, September.
    17. Zhi, Qiang & Sun, Honghang & Li, Yanxi & Xu, Yurui & Su, Jun, 2014. "China’s solar photovoltaic policy: An analysis based on policy instruments," Applied Energy, Elsevier, vol. 129(C), pages 308-319.
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    1. Zhao, Xiaochun & Jiang, Mei & Wu, Zijun & Zhou, Ying, 2023. "Quantitative evaluation of China's energy security policy under the background of intensifying geopolitical conflicts: Based on PMC model," Resources Policy, Elsevier, vol. 85(PA).

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